Real-Time ECG and EMG Analysis for Biking Using Android-Based Mobile Devices

Richer R, Blank P, Schuldhaus D, Eskofier B (2014)


Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2014

Edited Volumes: Proceedings - 11th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2014

Pages Range: 104-108

Conference Proceedings Title: 2014 IEEE 11th International Conference on Wearable and Implantable Body Sensor Networks (BSN)

Event location: Zürich CH

URI: https://www.mad.tf.fau.de/files/2018/04/2014-Richer-BSN-Bikey.pdf

DOI: 10.1109/BSN.2014.20

Abstract

We developed an application for Android-based mobile devices that enables a real-time calculation of heart rate and cadence for biking. Therefore, both ECG and EMG data are acquired in real time by Shimmer sensors and transmitted via Bluetooth, as well as processed and evaluated on the mobile device. The ECG algorithm is based on the Pan-Tompkins algorithm for QRS-Detection and offers a heart beat detection rate of more than 94%. The EMG algorithm offers a treadle detection rate of more than 91%. The application's range of features is complemented by GPS data for the calculation of speed and location information. It is available for download and can for example be used for controlling the user's training status, for live training supervision and for the subsequent analysis of the various training runs.

Authors with CRIS profile

Additional Organisation(s)

Related research project(s)

How to cite

APA:

Richer, R., Blank, P., Schuldhaus, D., & Eskofier, B. (2014). Real-Time ECG and EMG Analysis for Biking Using Android-Based Mobile Devices. In 2014 IEEE 11th International Conference on Wearable and Implantable Body Sensor Networks (BSN) (pp. 104-108). Zürich, CH.

MLA:

Richer, Robert, et al. "Real-Time ECG and EMG Analysis for Biking Using Android-Based Mobile Devices." Proceedings of the 2014 IEEE 11th International Conference on Wearable and Implantable Body Sensor Networks (BSN), Zürich 2014. 104-108.

BibTeX: Download